class_docstr: Piecewise constant decay with warmup schedule.
code: def __init__(
      self,
      rescaled_lr,
      step_boundaries,
      lr_values,
      warmup_steps,
      compute_lr_on_cpu,
      name,
  ):
      super(PiecewiseConstantDecayWithWarmup, self).__init__()
  
      self.rescaled_lr = rescaled_lr
      if StrictVersion(tf.__version__) >= StrictVersion("2.13"):
          self.step_boundaries = [int(b) for b in step_boundaries]
      else:
          self.step_boundaries = step_boundaries
      self.lr_values = lr_values
      self.warmup_steps = warmup_steps
      self.compute_lr_on_cpu = compute_lr_on_cpu
      self.name = name
  
      self.learning_rate_ops_cache = {}
  
file_path: DALI/docs/examples/use_cases/tensorflow/resnet-n/nvutils/common.py
imports: import tensorflow
  from distutils.version import StrictVersion
label_desc: Use image node_id 1 to create a new PiecewiseConstantDecayWithWarmup object from inherited base classes: tf.keras.optimizers.schedules with example: obj = PiecewiseConstantDecayWithWarmup(rescaled_lr, step_boundaries, lr_values, warmup_steps, compute_lr_on_cpu, name)